1 Loading of data

1.1 Data set

First, we load, filter, and merge the data sets.

How does the data set looks like

1.2 Set tresholds

Applied thresholds are indicated by grey horizontal line.

1.2.1 Area

1.2.2 Mean Intensity

1.2.3 Intensity cytoplasm ring 10

1.2.4 Intensity cytoplasm ring 9

1.2.5 Mean intensity cytoplasm ring 10

1.2.6 Mean intensity cytoplasm ring 9

1.3 Counts per sample

Cell counts per cell line:

#data <- read.csv("results/tables/data_GLUT1.csv")
table(data$Metadata_SampleID)
## 
## i1JF-R1-018 iG3G-R1-039 i1E4-R1-003 iO3H-R1-005 i82A-R1-002 iJ2C-R1-015 
##        4103        4524        4367        3111        3246        4893 
## iM89-R1-005 iC99-R1-007 iR66-R1-007 iAY6-R1-003 iPX7-R1-001 i88H-R1-002 
##        2460        4069        3165        4235        4735        4610

Mean cell count:

mean(table(data$Metadata_SampleID))
## [1] 3959.833

2 Visualize mitochondrial parameters

Various GLUT parameters are visualized for each patient-derived cell line as well as for the disease state Mean Ctrl levels are indicated by grey horizontal line.

2.1 Cytoplasmic area

2.1.1 each sample

2.1.2 disease-state

2.2 Mean intensity

2.2.1 each sample

2.2.2 disease-state

2.3 Intensity cytoplasm ring 10

2.3.1 each sample

2.3.2 disease-state

2.4 Intensity cytoplasm ring 9

2.4.1 each sample

2.4.2 disease-state

2.5 Mean intensity cytoplasm ring 10

2.5.1 each sample

2.5.2 disease-state

2.6 Mean intensity cytoplasm ring 9

2.6.1 each sample

2.6.2 disease-state

3 Statistical testing using linear mixed effects models

Nested approach (“GLUT intensity” ~ Disease_state + (1 | Disease_state:Metadata_SampleID)) to compensate for dependencies within the groups.

3.1 Cytoplasmic area

## Linear mixed model fit by maximum likelihood  ['lmerMod']
## Formula: AreaShape_Area ~ Disease_state + (1 | Disease_state:Metadata_SampleID)
##    Data: data
## 
##       AIC       BIC    logLik  deviance  df.resid 
##  835598.5  835633.5 -417795.2  835590.5     47514 
## 
## Scaled residuals: 
##     Min      1Q  Median      3Q     Max 
## -1.6402 -0.7708 -0.2246  0.5846  3.5142 
## 
## Random effects:
##  Groups                          Name        Variance Std.Dev.
##  Disease_state:Metadata_SampleID (Intercept)   97635   312.5  
##  Residual                                    2534663  1592.1  
## Number of obs: 47518, groups:  Disease_state:Metadata_SampleID, 12
## 
## Fixed effects:
##                  Estimate Std. Error t value
## (Intercept)        3019.0      140.2  21.531
## Disease_statesPD    140.5      183.6   0.765
## 
## Correlation of Fixed Effects:
##             (Intr)
## Diss_sttsPD -0.764
## Analysis of Deviance Table (Type II Wald chisquare tests)
## 
## Response: AreaShape_Area
##                Chisq Df Pr(>Chisq)
## Disease_state 0.5853  1     0.4442

3.2 Mean intensity

## Linear mixed model fit by maximum likelihood  ['lmerMod']
## Formula: 
## Intensity_MeanIntensity_Corr_GLUT ~ Disease_state + (1 | Disease_state:Metadata_SampleID)
##    Data: data
## 
##      AIC      BIC   logLik deviance df.resid 
## -94657.8 -94622.7  47332.9 -94665.8    47514 
## 
## Scaled residuals: 
##     Min      1Q  Median      3Q     Max 
## -2.6721 -0.6875 -0.1376  0.5585  4.8577 
## 
## Random effects:
##  Groups                          Name        Variance Std.Dev.
##  Disease_state:Metadata_SampleID (Intercept) 0.001584 0.03980 
##  Residual                                    0.007972 0.08929 
## Number of obs: 47518, groups:  Disease_state:Metadata_SampleID, 12
## 
## Fixed effects:
##                  Estimate Std. Error t value
## (Intercept)       0.18188    0.01781   10.21
## Disease_statesPD  0.02029    0.02332    0.87
## 
## Correlation of Fixed Effects:
##             (Intr)
## Diss_sttsPD -0.764
## Analysis of Deviance Table (Type II Wald chisquare tests)
## 
## Response: Intensity_MeanIntensity_Corr_GLUT
##                Chisq Df Pr(>Chisq)
## Disease_state 0.7571  1     0.3842

3.3 Intensity cytoplasm ring 10

## Linear mixed model fit by maximum likelihood  ['lmerMod']
## Formula: RadialDistribution_FracAtD_Corr_GLUT_10of10 ~ Disease_state +  
##     (1 | Disease_state:Metadata_SampleID)
##    Data: data
## 
##      AIC      BIC   logLik deviance df.resid 
## -99078.8 -99043.8  49543.4 -99086.8    47514 
## 
## Scaled residuals: 
##     Min      1Q  Median      3Q     Max 
## -2.5429 -0.7175 -0.1491  0.5679  4.1755 
## 
## Random effects:
##  Groups                          Name        Variance  Std.Dev.
##  Disease_state:Metadata_SampleID (Intercept) 0.0001596 0.01263 
##  Residual                                    0.0072682 0.08525 
## Number of obs: 47518, groups:  Disease_state:Metadata_SampleID, 12
## 
## Fixed effects:
##                   Estimate Std. Error t value
## (Intercept)       0.390555   0.005684  68.717
## Disease_statesPD -0.008012   0.007441  -1.077
## 
## Correlation of Fixed Effects:
##             (Intr)
## Diss_sttsPD -0.764
## Analysis of Deviance Table (Type II Wald chisquare tests)
## 
## Response: RadialDistribution_FracAtD_Corr_GLUT_10of10
##                Chisq Df Pr(>Chisq)
## Disease_state 1.1593  1     0.2816

3.4 Intensity cytoplasm ring 9

## Linear mixed model fit by maximum likelihood  ['lmerMod']
## Formula: RadialDistribution_FracAtD_Corr_GLUT_9of10 ~ Disease_state +  
##     (1 | Disease_state:Metadata_SampleID)
##    Data: data
## 
##       AIC       BIC    logLik  deviance  df.resid 
## -154503.3 -154468.2   77255.7 -154511.3     47514 
## 
## Scaled residuals: 
##     Min      1Q  Median      3Q     Max 
## -3.8578 -0.7212 -0.0388  0.6805  4.2054 
## 
## Random effects:
##  Groups                          Name        Variance  Std.Dev.
##  Disease_state:Metadata_SampleID (Intercept) 5.243e-05 0.007241
##  Residual                                    2.264e-03 0.047581
## Number of obs: 47518, groups:  Disease_state:Metadata_SampleID, 12
## 
## Fixed effects:
##                   Estimate Std. Error t value
## (Intercept)       0.349604   0.003257 107.347
## Disease_statesPD -0.002720   0.004264  -0.638
## 
## Correlation of Fixed Effects:
##             (Intr)
## Diss_sttsPD -0.764
## Analysis of Deviance Table (Type II Wald chisquare tests)
## 
## Response: RadialDistribution_FracAtD_Corr_GLUT_9of10
##               Chisq Df Pr(>Chisq)
## Disease_state 0.407  1     0.5235

3.5 Mean intensity cytoplasm ring 10

## Linear mixed model fit by maximum likelihood  ['lmerMod']
## Formula: RadialDistribution_MeanFrac_Corr_GLUT_10of10 ~ Disease_state +  
##     (1 | Disease_state:Metadata_SampleID)
##    Data: data
## 
##       AIC       BIC    logLik  deviance  df.resid 
## -123752.0 -123716.9   61880.0 -123760.0     47514 
## 
## Scaled residuals: 
##     Min      1Q  Median      3Q     Max 
## -4.2305 -0.5778  0.0536  0.6169  4.0459 
## 
## Random effects:
##  Groups                          Name        Variance  Std.Dev.
##  Disease_state:Metadata_SampleID (Intercept) 0.0001641 0.01281 
##  Residual                                    0.0043238 0.06576 
## Number of obs: 47518, groups:  Disease_state:Metadata_SampleID, 12
## 
## Fixed effects:
##                  Estimate Std. Error t value
## (Intercept)      0.951528   0.005749 165.525
## Disease_statesPD 0.004580   0.007527   0.609
## 
## Correlation of Fixed Effects:
##             (Intr)
## Diss_sttsPD -0.764
## Analysis of Deviance Table (Type II Wald chisquare tests)
## 
## Response: RadialDistribution_MeanFrac_Corr_GLUT_10of10
##                Chisq Df Pr(>Chisq)
## Disease_state 0.3703  1     0.5428

3.6 Mean intensity cytoplasm ring 9

## Linear mixed model fit by maximum likelihood  ['lmerMod']
## Formula: RadialDistribution_MeanFrac_Corr_GLUT_9of10 ~ Disease_state +  
##     (1 | Disease_state:Metadata_SampleID)
##    Data: data
## 
##       AIC       BIC    logLik  deviance  df.resid 
## -169325.0 -169289.9   84666.5 -169333.0     47514 
## 
## Scaled residuals: 
##     Min      1Q  Median      3Q     Max 
## -4.1837 -0.5958 -0.0711  0.5240  4.4423 
## 
## Random effects:
##  Groups                          Name        Variance  Std.Dev.
##  Disease_state:Metadata_SampleID (Intercept) 1.593e-05 0.003991
##  Residual                                    1.658e-03 0.040714
## Number of obs: 47518, groups:  Disease_state:Metadata_SampleID, 12
## 
## Fixed effects:
##                   Estimate Std. Error t value
## (Intercept)       1.019370   0.001809 563.383
## Disease_statesPD -0.001513   0.002369  -0.639
## 
## Correlation of Fixed Effects:
##             (Intr)
## Diss_sttsPD -0.764
## Analysis of Deviance Table (Type II Wald chisquare tests)
## 
## Response: RadialDistribution_MeanFrac_Corr_GLUT_9of10
##                Chisq Df Pr(>Chisq)
## Disease_state 0.4079  1      0.523